Ziad Youssfi

Ziad Youssfi
Associate Professor of Electrical and Computer Engineering
James Lehr Kennedy 276
525 South Main Street, Ada, OH, 45810
Academic Credentials
NVIDIA Deep Learning Institute Ambassador, Deep Learning & CUDA
Research Interests
Deep learning, Computer Architecture, Parallel Processing, Embedded Systems
Employee degree:

BS, Michigan State University

MS, Michigan State University

PHD, Michigan State University


My expertise includes the areas of deep learning, software development, embedded systems and robotics, computer architecture, and parallel processing. I teach by getting to know my students, emphasizing feedback, connecting concepts to the real world, and providing a multidisciplinary perspective. I am constantly fascinated by the power of technological innovations to address critical societal needs.

Through my career, in industry and academia, I have promoted innovation. At Intel, I developed new techniques to validate transistor operations in the Pentium Pro. For my PhD, I created an algorithm to throttle processor power consumption based on instruction parallelism. During my PhD at Michigan State, I developed a web application to streamline the University’s accounting. At Ohio Northern, I led curricular reform for electrical and computer engineering and computer science. In my research, I devised new parallel algorithms on GPUs for image processing. In all my projects, I consider the intersection between function and aesthetic form for optimal design.


Recent Scholarship

  1. Ziad Youssfi and Firas Hassan, Bryce Gray and John Merkel, "Fast Restoring of High Dynamic Range Image Appearance for Multi-Partial Reset Sensor," Electronic Imaging Conference, San Jose, CA, January 2019

  2. Ziad Youssfi and Firas Hassan, “Speeding Up Tone Mapping Operators, Exploiting Parallelism for Real-Time, High Dynamic Range Video,” IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), Boston, MA, 2017

  3. Ziad Youssfi, “Making Operating Systems More Appetizing with the Raspberry Pi,” IEEE Frontiers in Education (FiE) National Conference, Indianapolis, IN, 2017

Classes Taught

  • Deep Learning
  • Computer Architecture
  • Embedded Real-Time Applications
  • Operating Systems (inc. Parallel Processing)
  • Maker Engineering
  • VLSI (Very Large Scale Integration)
  • Programming C/C++


  • Ohio Northern University, Professor Henry Horldt Outstanding Teacher Award, T.J. Smull College of Engineering, 2018-2019
  • Ohio Northern University, Endowed Alter Chair Award, Department of Electrical & Computer Engineering and Computer Science, 2018-2019
  • Ohio Magazine Recognition for Outstanding Achievements in Teaching, 2019
  • University of Western Ontario, Teaching Honor Roll for Excellence in Teaching, University Students' Council, 2012-2013
  • Intel Corporation, Spontaneous Recognition Award
  • Motorola University Design Competition Recognition Award, Michigan State University